William S. Hayes

4.8k total citations
14 papers, 886 citations indexed

About

William S. Hayes is a scholar working on Molecular Biology, Artificial Intelligence and Computational Theory and Mathematics. According to data from OpenAlex, William S. Hayes has authored 14 papers receiving a total of 886 indexed citations (citations by other indexed papers that have themselves been cited), including 10 papers in Molecular Biology, 2 papers in Artificial Intelligence and 2 papers in Computational Theory and Mathematics. Recurrent topics in William S. Hayes's work include Genomics and Phylogenetic Studies (7 papers), Machine Learning in Bioinformatics (4 papers) and Biomedical Text Mining and Ontologies (4 papers). William S. Hayes is often cited by papers focused on Genomics and Phylogenetic Studies (7 papers), Machine Learning in Bioinformatics (4 papers) and Biomedical Text Mining and Ontologies (4 papers). William S. Hayes collaborates with scholars based in United States, Greece and Sweden. William S. Hayes's co-authors include Elaine N. Rubinstein, Michael R. Harwell, Mark Borodovsky, Nigel P. Brown, Roman L. Tatusov, Arcady Mushegian, Eugene V. Koonin, Peer Bork, Kenneth E. Rudd and Wyeth W. Wasserman and has published in prestigious journals such as Nucleic Acids Research, Current Biology and Genome Research.

In The Last Decade

William S. Hayes

13 papers receiving 842 citations

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
William S. Hayes United States 9 407 116 97 80 69 14 886
Igor Zwir United States 23 474 1.2× 370 3.2× 31 0.3× 104 1.3× 123 1.8× 51 1.5k
Myra L. Samuels United States 11 106 0.3× 75 0.6× 110 1.1× 68 0.8× 18 0.3× 25 714
Geert De Soete Belgium 20 368 0.9× 41 0.4× 111 1.1× 216 2.7× 305 4.4× 56 1.8k
Ian Saunders Australia 17 155 0.4× 199 1.7× 136 1.4× 36 0.5× 205 3.0× 58 1.2k
Michael Tessler United States 18 293 0.7× 90 0.8× 21 0.2× 303 3.8× 167 2.4× 69 1.2k
Luana Micallef Finland 11 154 0.4× 32 0.3× 26 0.3× 43 0.5× 44 0.6× 25 902
Estelle Russek United States 12 58 0.1× 42 0.4× 61 0.6× 134 1.7× 42 0.6× 22 844
James E. Johnson United States 22 604 1.5× 46 0.4× 21 0.2× 104 1.3× 85 1.2× 109 1.6k
Marjan Sjerps Netherlands 17 159 0.4× 303 2.6× 41 0.4× 76 0.9× 15 0.2× 60 843
Michael Klein Germany 20 161 0.4× 121 1.0× 7 0.1× 85 1.1× 78 1.1× 69 886

Countries citing papers authored by William S. Hayes

Since Specialization
Citations

This map shows the geographic impact of William S. Hayes's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by William S. Hayes with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites William S. Hayes more than expected).

Fields of papers citing papers by William S. Hayes

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by William S. Hayes. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by William S. Hayes. The network helps show where William S. Hayes may publish in the future.

Co-authorship network of co-authors of William S. Hayes

This figure shows the co-authorship network connecting the top 25 collaborators of William S. Hayes. A scholar is included among the top collaborators of William S. Hayes based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with William S. Hayes. William S. Hayes is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

14 of 14 papers shown
1.
Talikka, Marja, William S. Hayes, Martin Hofmann‐Apitius, et al.. (2017). Novel approaches to develop community-built biological network models for potential drug discovery. Expert Opinion on Drug Discovery. 12(8). 1–9. 8 indexed citations
2.
Zhang, Pengyi, Yan Qu, Chen Huang, et al.. (2010). Collaborative identification and annotation of government deep web resources. 285–286. 1 indexed citations
3.
Roberts, Phoebe M. & William S. Hayes. (2007). INFORMATION NEEDS AND THE ROLE OF TEXT MINING IN DRUG DEVELOPMENT. PubMed. 592–603. 11 indexed citations
4.
Podowski, Raf M., et al.. (2005). SUREGENE, A SCALABLE SYSTEM FOR AUTOMATED TERM DISAMBIGUATION OF GENE AND PROTEIN NAMES. Journal of Bioinformatics and Computational Biology. 3(3). 743–770. 9 indexed citations
5.
Roberts, Phoebe M. & William S. Hayes. (2005). Advances in text analytics for drug discovery.. PubMed. 8(3). 323–8. 1 indexed citations
6.
Lenhard, Boris, William S. Hayes, & Wyeth W. Wasserman. (2001). GeneLynx: A Gene-Centric Portal to the Human Genome. Genome Research. 11(12). 2151–2157. 43 indexed citations
7.
Hannenhalli, Sridhar, William S. Hayes, Artemis G. Hatzigeorgiou, & James W. Fickett. (1999). Bacterial start site prediction. Nucleic Acids Research. 27(17). 3577–3582. 35 indexed citations
8.
Hayes, William S. & Mark Borodovsky. (1998). How to Interpret an Anonymous Bacterial Genome: Machine Learning Approach to Gene Identification. Genome Research. 8(11). 1154–1171. 84 indexed citations
9.
Hirosawa, Makoto, Katsumi Isono, William S. Hayes, & Mark Borodovsky. (1997). Gene Identification and Classification in the Synechocystis Genomic Sequence by Recursive Gene Mark Analysis. DNA sequence. 8(1-2). 17–29. 14 indexed citations
10.
Tatusov, Roman L., Arcady Mushegian, Peer Bork, et al.. (1996). Metabolism and evolution of Haemophilus influenzae deduced from a whole-genome comparison with Escherichia coli. Current Biology. 6(3). 279–291. 242 indexed citations
11.
Hayes, William S., et al.. (1996). Applications of GeneMark in multispecies environments.. PubMed. 4. 165–75. 7 indexed citations
12.
Harwell, Michael R., et al.. (1992). Summarizing Monte Carlo results in methodological research: The fixed effects single- and two-factor ANOVA cases. Journal of Educational Statistics. 17. 315–339. 1 indexed citations
13.
Harwell, Michael R., et al.. (1992). Summarizing Monte Carlo Results in Methodological Research: The One- and Two-Factor Fixed Effects ANOVA Cases. Journal of Educational Statistics. 17(4). 315–315. 76 indexed citations
14.
Harwell, Michael R., et al.. (1992). Summarizing Monte Carlo Results in Methodological Research: The One- and Two-Factor Fixed Effects ANOVA Cases. Journal of Educational Statistics. 17(4). 315–339. 354 indexed citations

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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